NDLI: Generalized stochastic spiking neuron model and extended spike response model in spatial-temporal pulse pattern detection task

Content Provider	Springer Nature Link
Author	Sinyavskiy, O. Y. Kobrin, A. I.
Copyright Year	2010
Abstract	A generalized model of spiking neuron is proposed as a non-stationary stochastic spike sequences processing unit. The generalized spiking neuron model is described with a conditional spike generation probability distribution and with a state evolution operator. An information theory language is used for the convenient neuron’s learning tasks description. The problem of spiking neuron learning with the teacher is solved using information entropy minimization algorithm. A particular implementation of generalized model using stochastic Spike Response Model with alpha-functions set is provided. A task of time delay maintenance between input and output spikes and a task of detecting of a spiking pattern in a noisy stream of pulse signals are considered using extended SRM neuron. It is shown that after the using of the proposed learning method spiking neuron became capable to detect a spatial-temporal pulse pattern and to serve as an adaptive delay unit.
Starting Page	300
Ending Page	309
Page Count	10
File Format	PDF
ISSN	1060992X
Journal	Optical Memory and Neural Networks
Volume Number	19
Issue Number	4
e-ISSN	19347898
Language	English
Publisher	Allerton Press, Inc.
Publisher Date	2011-01-20
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	spiking neuron neuron models spiking neuron learning information theory information entropy Complexity Information Storage and Retrieval
Content Type	Text
Resource Type	Article
Subject	Computer Science Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering

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